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Control system engineering is a multidisciplinary discipline that applies automatic control theory to design systems with desired behaviors in control environments. Automatic control theory has played a vital role in the advancement of engineering and science. It has become an essential and integral part of modern industrial and manufacturing processes. Today, the requirements for control precision have increased, and real systems have become more complex. In control engineering and all other engineering disciplines, the impact of advanced mathematical and computational methods is rapidly increasing. Advanced mathematical methods are needed because real-world control systems need to comply with several conditions related to product quality and safety constraints that have to be taken into account in the problem formulation. Conversely, the increment in mathematical complexity has an impact on the computational aspects related to numerical simulation and practical implementation of the algorithms, where a balance must also be maintained between implementation costs and the performance of the control system. This book is a comprehensive set of articles reflecting recent advances in developing and applying advanced mathematics and computational applications in control system engineering.

doubly fed induction generator --- PI tuning --- LCL-filter --- passive damping --- advanced metaheuristics --- Bonferroni–Dunn and Friedman’s tests --- resistance spot welding --- dynamic resistance model --- adaptive control --- energy savings --- adaptive disturbance rejection controller --- hybrid systems --- state constraint --- worm robot --- bio-inspired robots --- Streeter–Phelps model --- fractional-order control --- high observers --- river monitoring --- 3 DOF crane --- convex systems --- fault-tolerant control --- robust control --- qLPV systems --- Takagi–Sugeno systems --- chaos --- synchronization --- FPGA --- UDS --- distillation column heating actuator --- Buck-Boost converter --- Takagi–Sugeno model --- fuzzy observer with sliding modes --- nonlinear optimization --- turbulent flow --- friction factor --- pipe roughness --- minor losses --- PID control and variants --- Intelligent control techniques --- neural control --- brushless DC electric motors --- sensors and virtual instruments --- analysis and treatment of signals --- n/a --- Bonferroni-Dunn and Friedman's tests --- Streeter-Phelps model --- Takagi-Sugeno systems --- Takagi-Sugeno model